Python hparams.hparams.power() Examples
The following are 27
code examples of hparams.hparams.power().
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Example #1
Source File: audio.py From arabic-tacotron-tts with MIT License | 5 votes |
def _db_to_amp(x): return np.power(10.0, x * 0.05)
Example #2
Source File: audio.py From Tacotron2-PyTorch with MIT License | 5 votes |
def _db_to_amp(x): return np.power(10.0, x * 0.05)
Example #3
Source File: audio.py From Tacotron2-PyTorch with MIT License | 5 votes |
def inv_melspectrogram(spectrogram): mel = _db_to_amp(_denormalize(spectrogram) + hps.ref_level_db) S = _mel_to_linear(mel) return inv_preemphasis(_griffin_lim(S ** hps.power))
Example #4
Source File: audio.py From Tacotron2-PyTorch with MIT License | 5 votes |
def inv_spectrogram(spectrogram): '''Converts spectrogram to waveform using librosa''' S = _db_to_amp(_denormalize(spectrogram) + hps.ref_level_db) # Convert back to linear return inv_preemphasis(_griffin_lim(S ** hps.power)) # Reconstruct phase
Example #5
Source File: audio.py From gmvae_tacotron with MIT License | 5 votes |
def _db_to_amp(x): return np.power(10.0, (x) * 0.05)
Example #6
Source File: audio.py From gmvae_tacotron with MIT License | 5 votes |
def inv_mel_spectrogram(mel_spectrogram): '''Converts mel spectrogram to waveform using librosa''' if hparams.mel_normalization: D = _denormalize(mel_spectrogram) else: D = mel_spectrogram S = _mel_to_linear(_db_to_amp(D + hparams.ref_level_db)) # Convert back to linear return _griffin_lim(S ** hparams.power)
Example #7
Source File: audio.py From gmvae_tacotron with MIT License | 5 votes |
def _db_to_amp(x): return np.power(10.0, (x) * 0.05)
Example #8
Source File: audio.py From gmvae_tacotron with MIT License | 5 votes |
def inv_mel_spectrogram(mel_spectrogram): '''Converts mel spectrogram to waveform using librosa''' if hparams.signal_normalization: D = _denormalize(mel_spectrogram) else: D = mel_spectrogram S = _mel_to_linear(_db_to_amp(D + hparams.ref_level_db)) # Convert back to linear return _griffin_lim(S ** hparams.power)
Example #9
Source File: audio.py From gmvae_tacotron with MIT License | 5 votes |
def inv_linear_spectrogram(linear_spectrogram): '''Converts linear spectrogram to waveform using librosa''' if hparams.signal_normalization: D = _denormalize(linear_spectrogram) else: D = linear_spectrogram S = _db_to_amp(D + hparams.ref_level_db) #Convert back to linear return _griffin_lim(S ** hparams.power)
Example #10
Source File: audio.py From WaveRNN-Pytorch with MIT License | 5 votes |
def _db_to_amp(x): return np.power(10.0, x * 0.05)
Example #11
Source File: audio.py From WaveRNN-Pytorch with MIT License | 5 votes |
def inv_spectrogram(spectrogram): '''Converts spectrogram to waveform using librosa''' S = _db_to_amp(_denormalize(spectrogram) + hparams.ref_level_db) # Convert back to linear processor = _lws_processor() D = processor.run_lws(S.astype(np.float64).T ** hparams.power) y = processor.istft(D).astype(np.float32) return inv_preemphasis(y)
Example #12
Source File: audio.py From tacotron with MIT License | 5 votes |
def _db_to_amp(x): return np.power(10.0, x * 0.05)
Example #13
Source File: audio.py From tacotron with MIT License | 5 votes |
def inv_spectrogram_tensorflow(spectrogram): '''Builds computational graph to convert spectrogram to waveform using TensorFlow. Unlike inv_spectrogram, this does NOT invert the preemphasis. The caller should call inv_preemphasis on the output after running the graph. ''' S = _db_to_amp_tensorflow(_denormalize_tensorflow(spectrogram) + hparams.ref_level_db) return _griffin_lim_tensorflow(tf.pow(S, hparams.power))
Example #14
Source File: audio.py From tacotron with MIT License | 5 votes |
def inv_spectrogram(spectrogram): '''Converts spectrogram to waveform using librosa''' S = _db_to_amp(_denormalize(spectrogram) + hparams.ref_level_db) # Convert back to linear return inv_preemphasis(_griffin_lim(S ** hparams.power)) # Reconstruct phase
Example #15
Source File: audio.py From Griffin_lim with MIT License | 5 votes |
def inv_spectrogram(spectrogram): S = _db_to_amp(_denormalize(spectrogram) + hparams.ref_level_db) # Convert back to linear return _inv_preemphasis(_griffin_lim(S ** hparams.power)) # Reconstruct phase
Example #16
Source File: audio.py From arabic-tacotron-tts with MIT License | 5 votes |
def inv_spectrogram_tensorflow(spectrogram): '''Builds computational graph to convert spectrogram to waveform using TensorFlow. Unlike inv_spectrogram, this does NOT invert the preemphasis. The caller should call inv_preemphasis on the output after running the graph. ''' S = _db_to_amp_tensorflow(_denormalize_tensorflow(spectrogram) + hparams.ref_level_db) return _griffin_lim_tensorflow(tf.pow(S, hparams.power))
Example #17
Source File: audio.py From arabic-tacotron-tts with MIT License | 5 votes |
def inv_spectrogram(spectrogram): '''Converts spectrogram to waveform using librosa''' S = _db_to_amp(_denormalize(spectrogram) + hparams.ref_level_db) # Convert back to linear return inv_preemphasis(_griffin_lim(S ** hparams.power)) # Reconstruct phase
Example #18
Source File: audio.py From vae_tacotron2 with MIT License | 5 votes |
def _db_to_amp(x): return np.power(10.0, (x) * 0.05)
Example #19
Source File: audio.py From vae_tacotron2 with MIT License | 5 votes |
def inv_mel_spectrogram(mel_spectrogram): '''Converts mel spectrogram to waveform using librosa''' if hparams.mel_normalization: D = _denormalize(mel_spectrogram) else: D = mel_spectrogram S = _mel_to_linear(_db_to_amp(D + hparams.ref_level_db)) # Convert back to linear return _griffin_lim(S ** hparams.power)
Example #20
Source File: audio.py From vae_tacotron2 with MIT License | 5 votes |
def _db_to_amp(x): return np.power(10.0, (x) * 0.05)
Example #21
Source File: audio.py From vae_tacotron2 with MIT License | 5 votes |
def inv_mel_spectrogram(mel_spectrogram): '''Converts mel spectrogram to waveform using librosa''' if hparams.signal_normalization: D = _denormalize(mel_spectrogram) else: D = mel_spectrogram S = _mel_to_linear(_db_to_amp(D + hparams.ref_level_db)) # Convert back to linear return _griffin_lim(S ** hparams.power)
Example #22
Source File: audio.py From vae_tacotron2 with MIT License | 5 votes |
def inv_linear_spectrogram(linear_spectrogram): '''Converts linear spectrogram to waveform using librosa''' if hparams.signal_normalization: D = _denormalize(linear_spectrogram) else: D = linear_spectrogram S = _db_to_amp(D + hparams.ref_level_db) #Convert back to linear return _griffin_lim(S ** hparams.power)
Example #23
Source File: audio.py From vae_tacotron with MIT License | 5 votes |
def _db_to_amp(x): return np.power(10.0, x * 0.05)
Example #24
Source File: audio.py From vae_tacotron with MIT License | 5 votes |
def inv_spectrogram_tensorflow(spectrogram): '''Builds computational graph to convert spectrogram to waveform using TensorFlow. Unlike inv_spectrogram, this does NOT invert the preemphasis. The caller should call inv_preemphasis on the output after running the graph. ''' S = _db_to_amp_tensorflow(_denormalize_tensorflow(spectrogram) + hparams.ref_level_db) return _griffin_lim_tensorflow(tf.pow(S, hparams.power))
Example #25
Source File: audio.py From vae_tacotron with MIT License | 5 votes |
def inv_spectrogram(spectrogram): '''Converts spectrogram to waveform using librosa''' S = _db_to_amp(_denormalize(spectrogram) + hparams.ref_level_db) # Convert back to linear return inv_preemphasis(_griffin_lim(S ** hparams.power)) # Reconstruct phase
Example #26
Source File: griffin_lim.py From Griffin_lim with MIT License | 5 votes |
def inv_spectrogram(spectrogram): S = _db_to_amp(_denormalize(spectrogram) + hparams.ref_level_db) # Convert back to linear return _inv_preemphasis(spectrogram2wav(S ** hparams.power)) # Reconstruct phase
Example #27
Source File: audio.py From Griffin_lim with MIT License | 5 votes |
def _db_to_amp(x): return np.power(10.0, x * 0.05)